class_docstr: A column object, with only the methods and properties required by the
  interchange protocol defined.
  A column can contain one or more chunks. Each chunk can contain up to three
  buffers - a data buffer, a mask buffer (depending on null representation),
  and an offsets buffer (if variable-size binary; e.g., variable-length
  strings).
  Note: this Column object can only be produced by ``__dataframe__``, so
        doesn't need its own version or ``__column__`` protocol.
docstr: Return the buffer containing the offset values for variable-size binary
  data (e.g., variable-length strings) and the buffer's associated dtype.
  Raises NoBufferPresent if the data buffer does not have an associated
  offsets buffer.
docstr_tok: ["Return","the","buffer","containing","the","offset","values","for","variable-size","binary","data","(","e.g.",",","variable-length","strings",")","and","the","buffer","'s","associated","dtype",".","Raises","NoBufferPresent","if","the","data","buffer","does","not","have","an","associated","offsets","buffer","."]
code: def _get_offsets_buffer(self) -> tuple[PandasBuffer, Any]:
      """
      Return the buffer containing the offset values for variable-size binary
      data (e.g., variable-length strings) and the buffer's associated dtype.
      Raises NoBufferPresent if the data buffer does not have an associated
      offsets buffer.
      """
      if self.dtype[0] == DtypeKind.STRING:
          # For each string, we need to manually determine the next offset
          values = self._col.to_numpy()
          ptr = 0
          offsets = np.zeros(shape=(len(values) + 1,), dtype=np.int64)
          for i, v in enumerate(values):
              # For missing values (in this case, `np.nan` values)
              # we don't increment the pointer
              if isinstance(v, str):
                  b = v.encode(encoding="utf-8")
                  ptr += len(b)
  
              offsets[i + 1] = ptr
  
          # Convert the offsets to a Pandas "buffer" using
          # the NumPy array as the backing store
          buffer = PandasBuffer(offsets)
  
          # Assemble the buffer dtype info
          dtype = (
              DtypeKind.INT,
              64,
              ArrowCTypes.INT64,
              Endianness.NATIVE,
          )  # note: currently only support native endianness
      else:
          raise NoBufferPresent(
              "This column has a fixed-length dtype so "
              "it does not have an offsets buffer"
          )
  
      return buffer, dtype
  
imports: from __future__ import annotations
  from typing import Any
  import numpy
  from pandas._libs.lib import infer_dtype
  from pandas._libs.tslibs import iNaT
  from pandas.errors import NoBufferPresent
  from pandas.util._decorators import cache_readonly
  from pandas.core.dtypes.dtypes import ArrowDtype, DatetimeTZDtype
  import pandas
  from pandas.api.types import is_string_dtype
  from pandas.core.interchange.buffer import PandasBuffer
  from pandas.core.interchange.dataframe_protocol import Column, ColumnBuffers, ColumnNullType, DtypeKind
  from pandas.core.interchange.utils import ArrowCTypes, Endianness, dtype_to_arrow_c_fmt
label_desc: Use image node_id 15 for calling the PandasColumn obj's underlying member method code with example usage: obj._get_offsets_buffer() and returns: buffer,  dtype